scholarly journals Sustainability, Big Data and Mathematical Techniques: A Bibliometric Review

Mathematics ◽  
2021 ◽  
Vol 9 (20) ◽  
pp. 2557
Author(s):  
Matilde Lafuente-Lechuga ◽  
Javier Cifuentes-Faura ◽  
Ursula Faura-Martínez
Keyword(s):  
Big Data ◽  
Empirical Work ◽  
The United States ◽  
Social Dimension ◽  
City Region ◽  
Continuous Increase ◽  
Decision Methods ◽  
Bibliometric Review ◽  
Development Goals ◽  
Mathematical Techniques

This article has reviewed international research, up to the first half of 2021, focused on sustainability, big data and the mathematical techniques used for its analysis. In addition, a study of the spatial component (city, region, nation and beyond) of the works has been carried out and an analysis has been made of which Sustainable Development Goals (SDGs) have received the most attention. A bibliometric analysis and a fractal cluster analysis were performed on the papers published in the Web of Science. The results show a continuous increase in the number of published articles and citations over the whole period, demonstrating a growing interest in this topic. China, the United States and India are the most productive countries and there are more papers at the regional level. It has been found that the environmental dimension is the most studied and the least studied is the social dimension. The mathematical techniques used in the empirical work are mainly regression analysis, neural networks and multi-criteria decision methods. SDG9 and SDG11 are the most worked on. The trend shows a convergence in recent years towards big data applied to supply chains, Industry 4.0 and the achievement of sustainable cities.

Analytical Study on Big Data

2018 ◽  
Vol 8 (5) ◽  
pp. 75
Author(s):  
Vivek Raich ◽  
Pankaj Maurya
Keyword(s):  
Information Technology ◽  
Big Data ◽  
Decision Maker ◽  
Analytical Study ◽  
Large Data ◽  
Decision Makers ◽  
Continuous Increase ◽  
Analytic Methods ◽  
Data Store ◽  
Business Engineering

in the time of the Information Technology, the big data store is going on. Due to which, Huge amounts of data are available for decision makers, and this has resulted in the progress of information technology and its wide growth in many areas of business, engineering, medical, and scientific studies. Big data means that the size which is bigger in size, but there are several types, which are not easy to handle, technology is required to handle it. Due to continuous increase in the data in this way, it is important to study and manage these datasets by adjusting the requirements so that the necessary information can be obtained.The aim of this paper is to analyze some of the analytic methods and tools. Which can be applied to large data. In addition, the application of Big Data has been analyzed, using the Decision Maker working on big data and using enlightened information for different applications.

Appeals by the Prosecution

2018 ◽  
Author(s):  
Nancy J. King ◽  
Michael Heise
Keyword(s):  
Empirical Work ◽  
The United States ◽  
National Sample ◽  
Federal Courts ◽  
Court Of Appeals ◽  
High Courts ◽  
Extensive Information ◽  
State High Courts ◽  
State Prosecutors ◽  
Rate Of Success

Scholarly and public debates about criminal appeals have largely taken place in an empirical vacuum. This study builds on our prior empirical work exploring defense-initiated criminal appeals and focuses on criminal appeals by state and federal prosecutors. Exploiting data drawn from a recently released national sample of appeals by state prosecutors decided in 2010, as well as data from all appeals by federal prosecutors to the United States Court of Appeals terminated in the years 2011 through 2016, we provide a detailed snapshot of non-capital, direct appeals by prosecutors, including extensive information on crime type, claims raised, type of defense representation, oral argument and opinion type, as well judicial selection, merits review, and relief. Findings include a rate of success for state prosecutor appeals about four times greater than that for defense appeals (roughly 40% of appeals filed compared to 10%). The likelihood of success for state prosecutor-appellants appeared unrelated to the type of crime, claim, or defense counsel, whether review was mandatory or discretionary, or whether the appellate bench was selected by election rather than appointment. State high courts, unlike intermediate courts, did not decide these appeals under conditions of drastic asymmetry. Of discretionary criminal appeals reviewed on the merits by state high courts, 41% were prosecutor appeals. In federal courts, prosecutors voluntarily dismissed more than half the appeals they filed, but were significantly less likely to withdraw appeals from judgments of acquittal and new trial orders after the verdict than to withdraw appeals challenging other orders. Among appeals decided on the merits, federal prosecutors were significantly more likely to lose when facing a federal defender as an adversary compared to a CJA panel attorney.

Policy coherence for development and migration: Analyzing US and EU policies through the lens of normative transformation

2017 ◽  
Vol 7 (2) ◽  
pp. 5-33 ◽  
Author(s):  
Harlan Koff
Keyword(s):  
The United States ◽  
Development Aid ◽  
Policy Coherence ◽  
Migration Policies ◽  
The Sustainable Development ◽  
Transformative Development ◽  
Development Goals ◽  
Policy Coherence For Development ◽  
And Migration ◽  
Global Affairs

The European Union’s (EU) 2015–2016 “migration/asylum crisis” gave discussions over the relationships between migration, security and development renewed prominence in global affairs. In response to record migratory flows, the EU, like the United States (US), has implemented security responses to migration aimed at protecting territorial integrity. This article addresses the migration–security–development nexus through the lens of policy coherence for development (PCD). It compares EU and US migration policies within the framework of the “transformative development” associated with the Sustainable Development Goals. It contends that these donors have undermined transformative development through the regionalization of development aid, which has contributed to the securitization of both development and migration policies. Thus, the article contends that new mechanisms for change need to be identified. It introduces the notion of “normative coherence” and proposes a potential role for regional human rights courts in fostering migration-related PCD.Spanish abstract: La “crisis migratoria” de la Unión Europea (UE) del 2015–2016 arrojó discusiones sobre las relaciones entre migración, seguridad y desarrollo renovando su prominencia en los asuntos globales. La UE, como los Estados Unidos de América (EE.UU), ha implementado respuestas de seguridad a la migración dirigidas a proteger la integridad territorial. Este artículo se dirige al nexo entre migración, seguridad y desarrollo a través de la lente de la coherencia de políticas públicas para el desarrollo (CPD). Compara las políticas migratorias de UE y EE.UU dentro del marco del “desarrollo transformativo” asociado con los Objetivos de Desarrollo Sostenible. Sostiene que estos donantes han socavado el desarrollo transformativo mediante la regionalización de la ayuda al desarrollo, el cual ha contribuido a incorporar aspectos de seguridad. Así, el artículo sostiene que se requiere identificar nuevos mecanismos para el cambio. Se introduce la noción de “coherencia normativa” y propone el rol potencial de cortes regionales de derechos humanos para promover CPD relacionadas a la migración.French abstract: La crise migratoire 2015-2016 de l’Union Européenne (UE) a replacé les discussions en matière de migration, de sécurité et de développement dans une perspective globale renouvelée. En réponse aux flux sans précédent, l’UE tout comme les Etats-Unis (EU) ont développé des réponses sécuritaires, destinées à protéger leur intégrité territoriale. Cet article évoque la connexion entre la migration, la sécurité et le développement à travers l’optique de la cohérence des politiques publiques pour le développement (CPD). Il compare les politiques migratoires de l’UE et des EU à partir du cadre du « développement transformateur » associé aux ODD. Il révèle que ces donateurs ont saboté le développement transformateur à travers la régionalisation de l’aide au développement, ce qui a contribué à octroyer un impératif sécuritaire. Ainsi, l’article soutient que de nouveaux mécanismes doivent être identifiés. Il introduit la « cohérence normative » et propose un rôle potentiel pour les Cours régionales des droits humaines dans la perspective de promouvoir la CPD en matière de migration.

Big Data Driven Clinical Informatics & Surveillance (BDD_CIS) – A Multimodal Database Focused Clinical, Community, and Multi-Omics Surveillance Plan for COVID-19: A study Protocol (Preprint)

2020 ◽  
Author(s):  
Bankole Olatosi ◽  
Jiajia Zhang ◽  
Sharon Weissman ◽  
Zhenlong Li ◽  
Jianjun Hu ◽  
...  
Keyword(s):  
Big Data ◽  
South Carolina ◽  
Data Science ◽  
Age Groups ◽  
The Elderly ◽  
The United States ◽  
Data Sources ◽  
Patient Registries ◽  
Multiple Partner ◽  
Multimodal Data

BACKGROUND The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) remains a serious global pandemic. Currently, all age groups are at risk for infection but the elderly and persons with underlying health conditions are at higher risk of severe complications. In the United States (US), the pandemic curve is rapidly changing with over 6,786,352 cases and 199,024 deaths reported. South Carolina (SC) as of 9/21/2020 reported 138,624 cases and 3,212 deaths across the state. OBJECTIVE The growing availability of COVID-19 data provides a basis for deploying Big Data science to leverage multitudinal and multimodal data sources for incremental learning. Doing this requires the acquisition and collation of multiple data sources at the individual and county level. METHODS The population for the comprehensive database comes from statewide COVID-19 testing surveillance data (March 2020- till present) for all SC COVID-19 patients (N≈140,000). This project will 1) connect multiple partner data sources for prediction and intelligence gathering, 2) build a REDCap database that links de-identified multitudinal and multimodal data sources useful for machine learning and deep learning algorithms to enable further studies. Additional data will include hospital based COVID-19 patient registries, Health Sciences South Carolina (HSSC) data, data from the office of Revenue and Fiscal Affairs (RFA), and Area Health Resource Files (AHRF). RESULTS The project was funded as of June 2020 by the National Institutes for Health. CONCLUSIONS The development of such a linked and integrated database will allow for the identification of important predictors of short- and long-term clinical outcomes for SC COVID-19 patients using data science.

scholarly journals Validity of the “Big Data Tendency in Education” Scale as a Tool Helping to Reach Inclusive Social Development

2020 ◽  
Vol 12 (13) ◽  
pp. 5470 ◽  
Author(s):  
Antonio Matas-Terrón ◽  
Juan José Leiva-Olivencia ◽  
Pablo Daniel Franco-Caballero ◽  
Francisco José García-Aguilera
Keyword(s):  
Big Data ◽  
Inclusive Education ◽  
Sustainable Development Goals ◽  
Sustainable Society ◽  
Education Students ◽  
The Sustainable Development ◽  
Research Goal ◽  
Development Goals ◽  
Nonprobability Sample ◽  
Big Data Technology

Big Data technology can be a great resource for achieving the Sustainable Development Goals in a fair and inclusive manner; however, only recently have we begun to analyse its impact on education. This research goal was to analyse the psychometric characteristics of a scale to assess opinions that educators in training have about Big Data besides their related emotions. This is important, as it will be the educators of the future who will have to manage with Big Data at school. A nonprobability sample of 337 education students from Peru and Spain was counted. Internal consistency, as well as validity, were analysed through exploratory and confirmatory factorial analysis. The results show good psychometric values, highlighting as relevant a latent structure of six factors that includes emotional and cognitive dimensions. As a result, the profile defining the participants in relation to Big Data was identified. Finally, the implications of the Big Data for Inclusive Education in a sustainable society are discussed.

Examining Racial Discrimination’s Association With Depressive Symptoms Through Metadehumanization Among African Americans: Does Racial Identity Matter?

2020 ◽  
pp. 009579842098366
Author(s):  
Yara Mekawi ◽  
Natalie N. Watson-Singleton
Keyword(s):  
Depressive Symptoms ◽  
Racial Identity ◽  
African Americans ◽  
Racial Discrimination ◽  
Indirect Effect ◽  
Social Cognitive ◽  
Empirical Work ◽  
The United States ◽  
Racial Groups ◽  
Social Cognitive Theories

Though considerable empirical work has documented the ways in which African Americans are dehumanized by other racial groups, there is no research examining how perceiving dehumanization (i.e., metadehumanization) is associated with the mental health of African Americans. In this study, we examined the indirect effect of racial discrimination on depressive symptoms through metadehumanization and explored whether this indirect effect was contingent on racial identity (i.e., centrality, private regard). African American students completed measures in a university lab located in the Midwestern region of the United States ( N = 326; Mage = 19.7, 72.4% women). We found that the degree to which racial discrimination was indirectly associated with depressive symptoms through metadehumanization was contingent on racial identity dimensions. Specifically, the indirect effect of racial discrimination on depressive symptoms through metadehumanization was only significant for individuals who were relatively higher on centrality and private regard. This research suggests that the role of metadehumanization is stronger among African Americans who strongly identify with and have positive views of their racial group. We discuss these results in the context of social cognitive theories.

scholarly journals Application of big data in healthcare: examination of the military experience

2021 ◽  
Author(s):  
David Berry
Keyword(s):  
Big Data ◽  
Vietnam War ◽  
Business Models ◽  
Model Development ◽  
The United States ◽  
Practical Implementation ◽  
Systems Research ◽  
System Versus ◽  
Military Systems ◽  
The Military

AbstractHealthcare is fully embracing the promise of Big Data for improving performance and efficiency. Such a paradigm shift, however, brings many unforeseen impacts both positive and negative. Healthcare has largely looked at business models for inspiration to guide model development and practical implementation of Big Data. Business models, however, are limited in their application to healthcare as the two represent a complicated system versus a complex system respectively. Healthcare must, therefore, look toward other examples of complex systems to better gauge the potential impacts of Big Data. Military systems have many similarities with healthcare with a wealth of systems research, as well as practical field experience, from which healthcare can draw. The experience of the United States Military with Big Data during the Vietnam War is a case study with striking parallels to issues described in modern healthcare literature. Core principles can be extracted from this analysis that will need to be considered as healthcare seeks to integrate Big Data into its active operations.

scholarly journals Toward Sociocultural Indicators of Sustainable Healthy Diets

2021 ◽  
Vol 13 (13) ◽  
pp. 7226
Author(s):  
Jill Nicholls ◽  
Adam Drewnowski
Keyword(s):  
Sustainable Development ◽  
Food Systems ◽  
Research Priorities ◽  
Social Dimension ◽  
The Sustainable Development ◽  
Four Dimensions ◽  
Sustainable Diets ◽  
The Social ◽  
Healthy Diets ◽  
Development Goals

Balancing the social, economic and environmental priorities for public health is at the core of the United Nations (UN) approaches to sustainable development, including the Sustainable Development Goals (SDGs). The four dimensions of sustainable diets are often presented as health, society, economics, and the environment. Although sustainable diet research has focused on health and the environment, the social and economic dimensions of sustainable diets and food systems should not be forgotten. Some research priorities and sociocultural indicators for sustainable healthy diets and food systems are outlined in this report. The present goal is to improve integration of the social dimension into research on food and nutrition security.

scholarly journals Corporate Social Responsibility and Sustainability. A Bibliometric Analysis of Their Interrelations

2021 ◽  
Vol 13 (4) ◽  
pp. 1636 ◽  
Author(s):  
Víctor Meseguer-Sánchez ◽  
Francisco Jesús Gálvez-Sánchez ◽  
Gabriel López-Martínez ◽  
Valentín Molina-Moreno
Keyword(s):  
Sustainable Development ◽  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Global Economy ◽  
The United States ◽  
Social Dimension ◽  
Unequal Distribution ◽  
Distribution Of Wealth ◽  
Productive Author ◽  
Corporate Social

Traditional economic system has brought important negative implications regarding environmental development, as well as an unequal distribution of wealth, which has led to ecological disasters and population imbalances. Considering the existence of unequal opportunities and access to resources in a global economy, it would be relevant to study the interrelations between the concepts of Sustainability and Corporate Social Responsibility (CSR). Global and multifactorial issues require the review of fieldworks and their connections. From this perspective, the present research aims to analyze the relationships between the concepts of Corporate Social Responsibility and Sustainability in order to understand the advances of current scientific production and future lines of research. In this way, there is a considerable increase of interest in this line of research, highlighting García-Sánchez as the most productive author, Business, Management and Accounting as the most studied topic, and Sustainability Switzerland as the most productive journal. The country with the most publications and citations is the United States, and the most productive institution is Universidad de Salamanca. Future lines of research should focus on the social dimension and its possibilities in the field of Circular Economy. Finally, a line of research is proposed that also includes the proposals from the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals.

Persistence and Change in Asian Identity among Children of Intermarried Couples

1995 ◽  
Vol 38 (2) ◽  
pp. 175-194 ◽  
Author(s):  
Rogelio Saenz ◽  
Sean-Shong Hwang ◽  
Benigno E. Aguirre ◽  
Robert N. Anderson
Keyword(s):  
United States ◽  
Multilevel Model ◽  
Empirical Work ◽  
The United States ◽  
Ethnic Identities ◽  
Ethnic Identification ◽  
Asian Ethnicity ◽  
Several Variables ◽  
Asian Identity ◽  
Multiracial Children

In recent years, a significant amount of attention has been devoted to the survival of ethnicity among multiracial people in the United States. This concern is especially evident in the case of the offspring of Asian-Anglo couples. While scholars have speculated on the extent to which Asian ethnicity will continue to persist among multiracial children, little empirical work has addressed this concern. In this analysis, we use a multilevel model to examine the ethnic identification (as reported by parents) of children of Asian-Anglo couples. Data from the 1980 Public-Use Microdata Sample for California are used in the analysis. The results indicate that the majority of the children had Anglo ethnic identities. The multivariate findings also identify several variables that are related to children's ethnic identification.

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